Ecology Letters, (2004) 7: 601–613
doi: 10.1111/j.1461-0248.2004.00608.x
REVIEW
The metacommunity concept: a framework
for multi-scale community ecology
M. A. Leibold,1* M. Holyoak,2
N. Mouquet,3,4 P. Amarasekare,5
J. M. Chase,6 M. F. Hoopes,7
R. D. Holt,8 J. B. Shurin,9 R. Law,10
D. Tilman,11 M. Loreau12 and
A. Gonzalez13
Abstract
The metacommunity concept is an important way to think about linkages between
different spatial scales in ecology. Here we review current understanding about this
concept. We first investigate issues related to its definition as a set of local communities
that are linked by dispersal of multiple potentially interacting species. We then identify
four paradigms for metacommunities: the patch-dynamic view, the species-sorting view,
the mass effects view and the neutral view, that each emphasizes different processes of
potential importance in metacommunities. These have somewhat distinct intellectual
histories and we discuss elements related to their potential future synthesis. We then use
this framework to discuss why the concept is useful in modifying existing ecological
thinking and illustrate this with a number of both theoretical and empirical examples. As
ecologists strive to understand increasingly complex mechanisms and strive to work
across multiple scales of spatio-temporal organization, concepts like the metacommunity
can provide important insights that frequently contrast with those that would be
obtained with more conventional approaches based on local communities alone.
Keywords
Mass effects, metacommunity, neutral model, patch dynamics, species sorting.
Ecology Letters (2004) 7: 601–613
Community ecology as a field is concerned with explaining
the patterns of distribution, abundance and interaction of
species. Such patterns occur at different spatial scales and
can vary with the scale of observation, suggesting that
different principles might apply at different scales (e.g. Levin
1992; Rosenzweig 1995; Maurer 1999; Chase & Leibold
2002). Remarkably, however, much of formal community
theory is focused on a single scale, assuming that local
communities are closed and isolated. Within these local
communities, populations are assumed to interact directly by
affecting each other’s birth and death rates, as modelled by
population dynamic models such as the classic LotkaVolterra equations and their extensions (e.g. May 1973;
Pimm & Lawton 1978; McCann et al. 1998). It has been
1
Department of Integrative Biology, University of Texas at
Austin, Austin, TX 78712, USA
7
Department of Integrative Biology, University of California,
Berkeley, CA 94720, USA
2
8
of California, Davis, CA 95616, USA
32611, USA
3
9
Science and Information Technology, Florida State University,
University Blvd., Vancouver, BC, Canada V6T 1Z4
Tallahassee, FL 23206, USA
10
4
11
Montpellier II, Place Eugene Bataillon, CC065, 34095,
Montpellier Cedex 05, France
Minnesota, St. Paul, MN 55108, USA
12
Laboratoire d’Ecologie, UMR 7625, Ecole Normale Supérieure, 46
5
rue d’Ulm, 75230 Paris Cedex 05, France
1101 E. 57th St., Chicago, IL 60637, USA
13
6
Montreal, Quebec, Canada H3A 1B1
MO 63130, USA
*Correspondence: E-mail: mleibold@mail.utexas.edu
INTRODUCTION
Department of Environmental Science and Policy, University
Department of Biological Science, School of Computational
Present address: Equipe Hote-Parasite, ISEM, University of
Department of Ecology and Evolution, University of Chicago,
Department of Biology, Washington University, St. Louis,
Department of Zoology, University of Florida, Gainesville, FL
Department of Zoology, University of British Columbia, 6270
Department of Biology, University of York, York Y010 5YW, UK
Department of Ecology, Evolution and Behavior, University of
Department of Biology, McGill University, 1205 Docteur Penfield,
Ó2004 Blackwell Publishing Ltd/CNRS
602 M. A. Leibold et al.
recognized, however, that other ecological processes involving species interactions occur at other scales (Wiens 1989;
Levin 1992; Holt 1993; Maurer 1999; Hubbell 2001). For
example, species interactions can occur in a network of local
communities where they affect colonization probabilities
and extinction patterns at a larger scale than those typically
addressed by population dynamic equations (e.g. Levins &
Culver 1971; Vandermeer 1973; Crowley 1981; Holt 1997;
Mouquet & Loreau 2002, 2003). The interactions and
demography of local communities could also be influenced
by other kinds of spatial dynamics, such as the flow of
individuals that create mass effects (Shmida & Wilson 1985)
and source–sink dynamics (Holt 1985; Pulliam 1988). These
dynamics involve interactions among local communities at
larger scales that we refer to as metacommunities.
We define a metacommunity as a set of local communities
that are linked by dispersal of multiple potentially interacting
species (Gilpin & Hanski 1991; Wilson 1992). Metacommunity theory describes processes that occur at the
metacommunity scale and suggests novel ways of thinking
about species interactions. Here we evaluate current
knowledge about such metacommunity theory, and we
discuss how it can contribute to explanations of the patterns
of distribution, abundance and interaction of organisms at
local as well as regional (metacommunity) scales that are
larger than those addressed by more conventional community theory.
In the following synthesis, we review some simple aspects
of metacommunity theory that ask how the fact that local
communities are embedded in a larger regional biota affects
local phenomena and patterns of variation among local
communities. Embedding local communities within a
metacommunity is likely to result in various spatial
dynamics, which can alter local species diversity both
directly and indirectly by altering local community processes
that feed back to alter features of the regional biota. Most
previous theoretical investigations ignored how this larger
regional biota might be constrained (e.g. the fixed mainland
species pool in the equilibrium theory of island biogeography, MacArthur & Wilson 1967). Therefore we also ask how
metacommunity dynamics affect the attributes of these
larger regional biotas, and how this effect feeds back to
patterns of local variation. It is clear from the little work
done to date that answers to this second question are likely
to greatly alter how we interpret many ecological patterns
and phenomena.
DEFINING METACOMMUNITIES
Currently, the concept of the metacommunity is mostly
theoretical and has received relatively little empirical
attention. It is easy to define local communities wherein
species interact by affecting each other’s demographic rates
Ó2004 Blackwell Publishing Ltd/CNRS
and a metacommunity as a set of local communities that
exchange colonists of multiple species (modified from
Wilson 1992). This definition posits that there are at least
two fairly discrete levels of community integration. At the
local level, we can draw on a very large literature on species
interactions, including conventional Lotka-Volterra models
as well as their elaborations to account for nonlinear
interactions and trophic structure (e.g. Murdoch & Oaten
1975; Holt 1977; Kuno 1987; Abrams & Walters 1996; Holt
& Polis 1997), as well as food web interactions of the kind
that may be seen in more speciose local communities (e.g.
Holt et al. 1994; Leibold 1996; Holt & Polis 1997; McCann
et al. 1998; Holt 2002; Bolker et al. 2003). At the regional
level, dispersal among local communities occurs and can
occur with variable rates. When dispersal rates are low, the
primary effects will involve colonization events that can
regulate the assembly history of local communities and we
can draw on a sizeable literature that investigates these
phenomena (MacArthur & Wilson 1967; Diamond 1975;
Drake 1991; Law & Morton 1996; Belyea & Lancaster 1999;
Weiher & Keddy 1999; Chase 2003; Steiner & Leibold
2004). If dispersal rates are high, we can also investigate the
roles of mass effects (Shmida & Wilson 1985) and rescue
effects (Brown & Kodric-Brown 1977). These mass and
rescue effects modify both species abundance (e.g. source–
sink dynamics; Pulliam 1988) and species interactions (Holt
1985; Danielson 1991), and consequently both could affect
community structure and dynamics (Holt et al. 2003). For
species that are capable of driving another species locally
extinct (e.g. natural enemies or superior competitors)
metapopulation theory suggests that there are both lower
and upper bounds on interpatch dispersal rates at which
regional persistence of both species is possible (e.g. Kareiva
1990; Amarasekare & Nisbet 2001; Mouquet & Loreau
2002, 2003).
While still in an early developmental stage, metacommunity thinking has already led to its own terminology (a guide
is presented in Table 1), which is strongly influenced by
ideas that come from the study of metapopulations. In this
paper, we restrict ourselves only to metacommunity
definitions that consider space implicitly and not explicitly
(e.g. spatially explicit models where the location of
individuals is tracked). We recognize, however, that there
are some important phenomena that depend on spatially
determined dynamics that our approach will consequently
overlook. Another important feature which is omitted from
our definition of metacommunities, but which should be
considered as the field continues to expand, is that different
species will often have local population regulation and
exchange colonists at different scales. As an example,
individual lakes in a region with numerous lakes might
reasonably be considered to have fairly independent and
isolated local fish populations but some of their avian
The metacommunity concept 603
Table 1 Terms used to define scales of organization and population dynamics in metacommunities
Term
Ecological scales of organization
Population
Metapopulation
Community
Metacommunity
Descriptions of space
Patch
Microsite
Locality
Region
Types of dynamics
Spatial dynamics
Mass effect
Rescue effect
Source–sink effects
Colonization
Dispersal
Stochastic extinctions
Deterministic extinctions
Metacommunity dynamics
Definition
All individuals of a single species within a habitat patch
A set of local populations of a single species that are linked by dispersal (after Gilpin and Hanski 1991)
The individuals of all species that potentially interact within a single patch or local area of habitat
A set of local communities that are linked by dispersal of multiple interacting species (Wilson 1992)
A discrete area of habitat. Patches have variously been defined as microsites or localities
(Levins 1969; Tilman 1994; Amarasekare & Nisbet 2001; Mouquet & Loreau 2002). In this paper we
use the term analogously to localities, which are capable of holding populations or communities
A site that is capable of holding a single individual. Microsites are nested within localities
An area of habitat encompassing multiple microsites and capable of holding a local community
A large area of habitat containing multiple localities and capable of supporting a metacommunity. This
corresponds to the ÔmesoscaleÕ of Holt (1993)
Any mechanism by which the distribution or movement of individuals across space influences local
or regional population dynamics. Different types of dynamics are discussed by Holyoak & Ray (1999)
A mechanisms for spatial dynamics in which there is net flow of individuals created by differences
in population size (or density) in different patches (Shmida & Wilson 1985)
A mechanism for spatial dynamics in which there is the prevention of local extinction of species
by immigration (Brown & Kodric-Brown 1977)
A mechanism for spatial dynamics in which there is the enhancement of local populations by
immigration in ÔsinkÕ localities due to migration of individuals from other localities where emigration
results in lowered populations
A mechanism for spatial dynamics in which populations become established at sites from which they
were previously absent
Movement of individuals from a site (emigration) to another (immigration)
A mechanism whereby established local populations of component species become extinct for reasons
that are independent of the other species present or of deterministic change in patch quality. Among
other possibilities these include stochastic components associated with small populations and
extinctions due to stochastic environmental changes (i.e. disturbances) that can affect large
populations
A mechanism whereby established local populations of component species become extinct due
to deterministic aspects of patch quality or in the composition of the local community
The dynamics that arise within metacommunities. Logically, these consist of spatial dynamics,
community dynamics (multispecies interactions or the emergent properties arising from them within
communities), and the interaction of spatial and community dynamics. The term is best avoided
because its use detracts from the dynamical mechanisms
Types of model population or community structure
Classic (Levins) metapopulation A group of identical local populations with finite and equal probabilities of extinction
and recolonization – no rescue effects occur
Source–sink system
A system with habitat-specific demography such that some patches (source habitats) have a finite
growth rate of greater than unity and produce a net excess of individuals which migrate to sink
patches. Populations in sink habitats have finite growth rates of less than one and would decline to
extinction in the absence of immigration from sources (based on Holt 1985; Pulliam 1988)
Mainland–island system
A system with variation in local population size which influences the extinction probability
of populations. Systems are usually described as consisting of extinction-resistant mainland
populations and extinction-prone island populations (Boorman and Levitt 1973).
Open community
A community which experiences immigration and/or emigration
Closed community
A community that is isolated, receiving no immigrants and giving out no emigrants
Patch occupancy model
A model in which patches contain either individuals or populations of one or more species and where
local population sizes are not modelled
Spatially explicit model
A model in which the arrangement of patches or distance between patches can influence patterns
of movement and interaction
Ó2004 Blackwell Publishing Ltd/CNRS
604 M. A. Leibold et al.
Table 1 continued
Term
Spatially implicit model
Metacommunity paradigms
Patch dynamics perspective
Species-sorting perspective
Mass-effect perspective
Neutral perspective
Definition
A model in which the arrangement of patches and/or individuals does not influence the dynamics of
the system. Movement is assumed equally likely between all patches
A perspective that assumes that patches are identical and that each patch is capable of containing
populations. Patches may be occupied or unoccupied. Local species diversity is limited by dispersal.
Spatial dynamics are dominated by local extinction and colonization
A perspective that emphasizes the resource gradients or patch types cause sufficiently strong
differences in the local demography of species and the outcomes of local speciesÕ interactions that
patch quality and dispersal jointly affect local community composition. This perspective emphasizes
spatial niche separation above and beyond spatial dynamics. Dispersal is important because it allows
compositional changes to track changes in local environmental conditions
A perspective that focuses on the effect of immigration and emigration on local population dynamics.
In such a system species can be rescued from local competitive exclusion in communities where they
are bad competitors, by immigrate from communities where they are good competitors. This
perspective emphasizes the role that spatial dynamics affect local population densities
A perspective in which all species are similar in their competitive ability, movement and fitness
(Hubbell 2001). Population interactions among species consist of random walks that alter relative
frequencies of species. The dynamics of species diversity are then derived both from probabilities of
species loss (extinction, emigration) and gain (immigration, speciation).
predators probably have demographic rates that are regulated over larger spatial scales, involving sets of lakes.
It is also possible to imagine species interactions
occurring over more than two scales. In fact, many current
models of metacommunity dynamics, especially those
inspired by work on sessile taxa (e.g. plants), are based on
a three-level hierarchy (Table 1). At the smallest scale
microsites can hold a single individual. Microsites are nested
within localities that hold local communities similar to those in
conventional species interaction models. In turn, local
communities are connected to other such communities as
part of a metacommunity occupying a region. In much of the
literature, localities are often equivalent to habitat patches.
This distinction becomes blurred in patch occupancy
models (e.g. Levins 1969; Hastings 1980; Hubbell 2001;
Mouquet & Loreau 2002) where patches can be viewed
either as microsites or localities holding individuals or
populations. In this paper we use the term patch to be
equivalent to a locality capable of holding a local population
or community (Table 1).
Obviously, the application of these theoretical definitions
of metacommunities to real empirical situations is not
straightforward. Two of the biggest problems are that local
communities do not always have discrete boundaries and
that different species may respond to processes at different
scales. Nevertheless some systems probably approximate
these definitions better than others. Examples tend to fall
into three categories: (1) assemblages of discrete, permanent
Ó2004 Blackwell Publishing Ltd/CNRS
habitat patches, (2) temporary patches distinct from a
background habitat matrix but varying in position and
frequency with time and (3) permanent habitats with
indistinct boundaries.
Clusters of oceanic islands exemplify the first category,
with oceans providing barriers to dispersal to different
degrees depending on the taxa considered (Mehranvar &
Jackson 2001). The vast literature on island biogeography is
a starting point for finding many potential examples of
communities where isolation at certain spatial scales and
habitat area has been shown to influence species diversity,
although other community properties have not been studied
as extensively. Similarly, ponds and lakes often have biotas
that are strongly bounded by terrestrial habitat, but again the
degree to which the intervening terrestrial habitat is a barrier
varies between taxa. One well-studied example of this first
kind derives from experimental work using carpets of
epilithic moss, containing a species-rich assemblage of
microarthropods; experiments showed that altering landscape connectivity influenced several community properties,
such as local and regional diversity and secondary productivity (Gilbert et al. 1998; Gonzalez et al. 1998; Gonzalez &
Chaneton 2002).
The second category consists of assemblages occupying
habitat patches that are temporary, which vary in position,
and are distinct from the intervening habitat matrix. Species
in these environments may be strongly regulated by traits
related to spatial dynamics such as dispersal (Harrison &
The metacommunity concept 605
Taylor 1997). For example, pitcher plants form temporary
patches of aquatic habitat, requiring dispersal of at least
some inhabitants, which range from bacteria to insects
(Kneitel & Miller 2002, 2003; Miller et al. 2002). The
inhabitants of water-filled tree holes (Kitching 2001) and
fungal fruiting bodies (Worthen et al. 1996) are other
potential examples of this kind of community. In cases
where habitat patches have continuity in space but suffer
frequent disturbances that can eliminate active populations
of the component community, dormancy may be another
important factor that can alter the consequent metacommunity dynamics.
The final category is the most problematic, consisting of
systems in which habitats are more permanent and
boundaries are less distinct. For example, coral reefs are
habitats containing species which operate over different
spatial scales due to differences in the degree of larval
retention (Roberts 1997), and because species respond to
various scales of productivity, currents and upwelling
(Cornell & Karlson 2000). In reefs the role of dispersal in
maintaining species diversity is generally unclear but is
hypothesized to be important by various authors (e.g.
Mumby 1999; Cornell & Karlson 2000). Even in situations
where there are only very diffuse boundaries between
habitat patches, e.g. grasslands and various other plant
communities, colonization-extinction dynamics or mass
effects may still influence community structure over some
spatial and temporal scales (e.g. Shmida & Wilson 1985;
Tilman 1994; Husband & Barrett 1996; Kessler 2000). In
such systems the degree to which spatial dynamics are
important is likely to vary with the degree of habitat
specialization, which influences the organismsÕ perception
of habitat size and isolation (Harrison 1997). Whether
models of metacommunity dynamics based on discrete local
communities can help us understand these situations is an
open question, but convergence of patterns of metacommunity structure (such as those described below) with more
conventional situations would indicate that they might.
FOUR SIMPLIFIED VIEWS OF METACOMMUNITIES
To date, theoretical and empirical work on metacommunities falls along four broad lines or approaches that we refer
to as the Ôpatch-dynamicÕ, Ôspecies-sortingÕ, Ômass-effectÕ and
ÔneutralÕ paradigms (Fig. 1).
The patch-dynamic paradigm
The first approach assumes that there are multiple identical
patches that undergo both stochastic and deterministic
extinctions that can be affected by interspecific interactions,
and that are counteracted by dispersal. Two approaches
have been used to model these kinds of dynamics. Often,
models based on patch dynamics are based on occupancy
formalisms in which patches are either vacant or are
occupied by populations at their equilibrium so that there is
an assumption of distinct time scales between local
dynamics and regional colonization-extinction dynamics. A
common limitation is that patches (or localities) are assumed
to be identical. The simplest version of this model considers
only regional coexistence in systems where species compete
for resources but no other kinds of species interactions
influence local dynamics, and local dynamics are not
explicitly considered (Levins & Culver 1971). For competitive metacommunities in a homogeneous environment,
regional coexistence is possible given an appropriate tradeoff between competitive ability and dispersal; such a
scenario is illustrated for two competing species in Fig. 1a.
Recent papers by Yu et al. (2001) and Yu & Wilson (2001)
also consider a trade-off between fecundity and dispersal
with similar conclusions. This classic two-level approach has
been re-scaled by Hastings (1980) and Tilman (1994), who
considered a single community divided into single-resource
patches (microsites rather than localities; Table 1) that
cannot contain more than one individual. Here, extinction
rates are re-interpreted as mortality rates and the results are
essentially the same: coexistence is possible given a
competition-colonization trade-off. Both these formalisms
give broadly similar results for the local and regional
coexistence discussed here. Different results can occur when
there are weak interactions or mutualisms involved
(Klausmeier 2001).
The effects of predator–prey interactions on regional
persistence has been considered in patch occupancy models
with patches containing individuals or populations (e.g.
Caswell 1978; McCauley et al. 1993) and also in models with
explicit local dynamics (e.g. Crowley 1981). Adding predators
that are capable of causing local extinction of prey leads to
constraints on the dispersal rates at which regional persistence is possible. Prey must colonize patches faster than they
are driven extinct and more rapidly than predators, and
persistence is only possible at intermediate dispersal rates
(reviewed in Kareiva 1990; Taylor 1990). Metapopulation
models have also considered two parasitoids and a single
host species (Hassell et al. 1994) resulting in constraints on
dispersal similar to competition models, but no published
patch dynamics models that we are aware of have evaluated
more complete community structures. One of the best
empirical examples of multispecies patch dynamics is
provided by the work on a total of 10 species, including a
butterfly, its host plants and parasitoids (Van Nouhuys &
Hanski 2002). This work builds on a strong tradition of patch
dynamics exemplified by Hanski and colleagues’s work on
butterfly metapopulations (Hanski 1998). A second potential
example is the lizards and spiders on Caribbean islands
investigated by Schoener & Spiller (1987, 1996).
Ó2004 Blackwell Publishing Ltd/CNRS
606 M. A. Leibold et al.
Figure 1 Schematic representation of the four paradigms for metacommunity theory for two competing species with populations A and B.
Arrows connect donor populations with potential colonization sites, shown as large boxes or ovals. Solid arrows indicate higher dispersal than
dashed arrows and either unidirectional movement (single-headed arrows) or bidirectional movement (double-headed arrows). The degree to
which a species is the competitive dominant in a site is shown by the matching of the smaller box or oval (denoting its habitat type niche) with
the site symbol. The four paradigms illustrated are (a) patch-dynamics, (b) species-sorting, (c) mass-effects and (d) neutral. In (a) the patchdynamics paradigm is shown with conditions that permit coexistence: a competition-colonization trade-off is illustrated with species A being a
superior competitor but species B being a superior colonist; the third patch is vacant and could become occupied by either species. In
(b) species are separated into spatial niches and dispersal is not sufficient to alter their distribution. In (c) mass effects cause species to be
present in both source and sink habitats; the smaller letters and symbols indicate smaller sized populations. In (d) all species are currently
present in all patches; species would gradually be lost from the region and would be replaced by speciation.
The species-sorting paradigm
The second approach builds on theories of community
change over environmental gradients (see Whittaker 1962)
and considers the effects of local abiotic features on
population vital rates and species interactions (Tilman 1982;
Leibold 1998; Chase & Leibold 2003). In this perspective,
local patches are viewed as heterogeneous in some factors
and the outcome of local species interactions depends on
aspects of the abiotic environment. If different species can
only inhabit exclusive habitat types, the resulting metacommunity can be broken down into two independent ones, but
Ó2004 Blackwell Publishing Ltd/CNRS
when individual species can inhabit multiple habitat types,
there are a variety of outcomes that reflect how species
interact at larger spatial scales. One way to model such
dynamics is to extend assembly models (e.g. Law & Morton
1996) to systems with multiple patch types. Like many
patch-dynamics models, this approach assumes that there is
a separation of time scales between local population
dynamics and colonization-extinction dynamics. Populations are assumed to go to their equilibrium behaviour (be it
a stable point or a more complex oscillating or complex
attractor) in between colonization events and before
environmental perturbations that might cause extinctions
The metacommunity concept 607
to occur. This approach focuses on trade-offs among
species that allow them to specialize on different patch types
(local conditions) rather than on possible trade-offs between
such traits and dispersal (as is found in the competitioncolonization trade-off commonly found in patch dynamics
models).
This species-sorting perspective has much in common
with traditional theory about niche separation and coexistence (Dobzhansky 1951; MacArthur 1958; Pianka 1966).
At larger spatial scales, however, metacommunity processes
are important in allowing local community composition to
track changes in the local environment (due to perturbations
or gradual environmental change, for example) in ways that
maintain the correspondence between local conditions and
composition. Law & Leibold (In press) show how speciessorting models can have different dynamics in a metacommunity framework than in more conventional assembly
models, one important difference is that metacommunity
dynamics in cases with endpoint dynamics that consist of
repeated cycles can be stabilized at the metacommunity
scale. Shurin et al. (2003) show that alternate stable local
communities are unlikely to occur in metacommunities
unless they have sufficient environmental heterogeneity
among patches. Metacommunity dynamics also constrain
attributes of the regional biota in important ways that relate
to ecological constraints at larger scales (see Leibold 1998;
Chase & Leibold 2003; Shurin et al. 2003). The result is that
species distributions are closely linked to local conditions
and largely independent of unrelated purely spatial effects
(Cottenie et al. 2003; Leibold and Norberg, in press).
Nevertheless, species sorting can still result in complex
dynamics because of the possibility of cyclical assembly
dynamics that are habitat-specific (e.g. Law & Morton 1996;
Steiner & Leibold 2004). In these situations communities go
through assembly cycles that repeat themselves. One case
that comes up in food web models is when a species from a
low trophic level serves to assemble a food chain that is
dependent on it and is excluded by competition with a
competitor that has no resident consumers. The new basal
species can then serve to assemble its own food chain that
may be reciprocally invaded and excluded by the first
species. Such food web assembly cycles involving species
sorting (matching of prey to consumers and vice versa)
appear in food web models of community assembly (Steiner
& Leibold 2004) where their occurrence is enhanced by
higher productivity.
Pond plankton appear to be a good example of such
metacommunities. In metacommunities consisting of ponds
in a biogeographically constrained region local communities
appear to be highly resistant to invasion by absent species
from the region unless there are significant perturbations
(Shurin 2000, 2001). This would indicate that local
communities have reached endpoint assembly configura-
tions. On the other hand, even under unusually high
immigration, species from other patch types seem to have
very little influence on these local communities (Cottenie
et al. 2003), indicating that local population dynamics are not
strongly influenced by such mass effects (see below).
Consequently there is good correspondence between local
composition and local abiotic conditions (e.g. Leibold 1999;
Cottenie et al. 2003) even after sudden environmental
changes have occurred (e.g. Cottenie et al. 2003).
The mass-effects paradigm
While the patch-dynamics and species-sorting paradigms
presume that there is a separation of time scales between
local dynamics and colonization-extinction dynamics,
important regional dynamics may also emerge when this is
not so, and local population dynamics are quantitatively
affected by dispersal. Such mass effects due to dispersal
require that different patches have different conditions at a
given time and be sufficiently connected that dispersal can
result in source–sink relations between populations in
different patches, and they can have potentially strong
influences on the relationships between local conditions and
community structure (Holt 1993; Mouquet & Loreau 2002,
2003). The role of dispersal is twofold. Immigration can
supplement local birth rates to enhance densities of local
populations beyond what might be expected in closed
communities and second, and emigration can enhance the
loss rates of local populations from that expected in closed
communities (Brown & Kodric-Brown 1977; Shmida &
Wilson 1985; see also Holyoak & Ray 1999). Such a scenario
is depicted in Fig. 1c.
For competing species there are two versions of the
model, one is a pure competitive weighted lottery in which
discrete changes in the number of individuals for a fixed
total population size are determined by probabilistic rules
related to relative population sizes and attributes (Chesson
1985; Iwasa & Roughgarden 1986; Mouquet & Loreau 2003)
and the other is based on the classical MacArthur model
of species competition (Levin 1974; Amarasekare 2000;
Amarasekare & Nisbet 2001). The two approaches
introduce a constraint of regional similarity; even though
coexisting species have to differ in their abilities to compete
in a particular patch type, they have to have compensating
differences in their abilities to compete and disperse to other
patch types that make them similar at the regional scale.
Coexistence in such a metacommunity is obtained through a
regional compensation of local competitive abilities: as a
consequence, species are locally different but regionally
similar (Mouquet & Loreau 2002). Mass effects allowing for
local coexistence however are constrained in complex ways
(Amarasekare & Nisbet 2001) because coexistence requires
spatial variance in fitness (competitive ability) but cannot
Ó2004 Blackwell Publishing Ltd/CNRS
608 M. A. Leibold et al.
occur if there is too much dispersal among patch types.
There are at least two artificial fragmentation experiments
that provide potential examples of empirical systems that
appear to fit this paradigm. Gonzalez et al. (1998) showed
that the provision of habitat corridors (presumably facilitating movement) reduced loss of species diversity in a system
consisting of microarthropods inhabiting moss patches on
stones. Holyoak (2000) demonstrated that the rate of species
loss was reduced by the presence of corridors in a food web
consisting of bacteria and four protist species food webs
and that a mass (rescue) effect was present for a basal protist
species. At very high dispersal rates, however, mass effects
can reduce coexistence in the regional metacommunity with
consequent parallel reduction of local diversity as the local
communities become homogenized (Mouquet & Loreau
2003), a prediction that corresponds with findings of Kneitel
& Miller (2003) and Forbes & Chase (2002).
The neutral paradigm
All the previous approaches presume that species differ
from each other in either their niche relations with local
factors and/or in their abilities to disperse or avoid local
extinctions (e.g. Fig. 1d). The dynamics that result depend
on the trade-offs that emerge from these assemblages and
their consequences at the local and regional scales. In the
absence of any such differences among species, the
behaviour of metacommunities can be different (Caswell
1976; Bell 2000; Hubbell 2001). Regardless of how likely
such equivalence might be, this ÔneutralÕ view can be
regarded as a null hypothesis for the other three views
described above (Bell 2001), but it may also describe
dynamics of some communities where species are close to
being equivalent or where transient dynamics are very long.
As an example, McPeek & Brown (2000) have investigated
differences between competing damselfly species and finds
rather little difference among some species, leaving the
neutral paradigm as a potential explanation for high species
diversity in this groups of insects.
In the absence of speciation or of immigration from
outside a metacommunity, a neutral model will eventually
lead to loss of all competing species but one via a slow
process of random walks to extinction (Chesson & Huntly
1997). Thus, in contrast to the other views described above
it cannot explain how local and regional diversity differ
without appeal to other processes. Hubbell (2001) has
explored the model in situations where speciation acts to
counteract the extinction process and points out that even
slow speciation rates can lead to very high sustained levels of
diversity in such metacommunities. Under these conditions
the neutral model has its own metacommunity dynamics
predominantly influenced by slow random patterns of
compositional change in space and through time.
Ó2004 Blackwell Publishing Ltd/CNRS
THE ROLE OF TRADE-OFFS AMONG SPECIES
TRAITS IN METACOMMUNITIES
The problem is that real ecological communities are
probably subject to both habitat variability and to local
stochastic or non-equilibrium dynamics. A synthetic perspective on metacommunities would be a great improvement in understanding how communities are structured by
the joint action of processes operating at both local and
regional scales (Amarasekare 2003; Kneitel & Chase 2004).
Clearly all four paradigms outlined above capture
interesting aspects of metacommunity dynamics. Further,
it is unlikely that all the species that interact in a given set of
real metacommunities will uniformly conform to any one of
these perspectives. Instead, it is likely that each of these sets
of processes will play interactive roles in structuring real
metacommunities. A synthetic perspective on these four
approaches is not currently at hand. However, the extent to
which real metacommunities will conform to the predictions
listed above will depend on how well the system conforms
to the assumptions of the models.
Assumptions in the four models are of at least two types.
First, the models make different assumptions about the
nature of differences among local sites. In the case of the
patch dynamic and neutral models, the assumptions are that
local sites do not differ in any respect except for the species
composition that exists at any given moment in time.
Alternatively the mass-effect and species-sorting perspectives assume that there are intrinsic differences among local
sites in their attributes so that different species might be
favoured at different sites.
Second, these models differ in the assumptions they make
about the ecological traits of species involved in the
metacommunity. In the neutral model, the assumption is
that there is no variation in these traits, and consequently no
covariation either. In the patch-dynamic models for
competitive metacommunities the assumption is that there
is sufficient variation in competitive ability, and that
covariance with dispersal is sufficiently negative to permit
regional coexistence. In the mass-effect and species-sorting
models, the assumptions are that there are trade-offs in the
abilities of species to perform well under different habitat
conditions. These considerations lead to the idea that a
synthesis of mass-effect and species-sorting perspectives is
probably most easily done, and indeed such synthesis has
already been suggested (Amarasekare & Nisbet 2001;
Mouquet & Loreau 2002, 2003; Amarasekare 2003).
More important, however, is that the behaviour of actual
metacommunities may depend strongly on how the species
pools have evolved (Shurin et al. 2000; Amarasekare 2003;
Leibold & Miller 2004). If there has not been the evolution
of trade-offs between dispersal and competitive ability for
example, then the predictions of the patch-dynamic model
The metacommunity concept 609
for competitive metacommunities will not be obtained even
if habitat patches do undergo temporal dynamics. Similarly,
if there has not been the evolution of trade-offs for alternate
resources, then the predictions of the species-sorting model
will not be obtained even if there is a lot of variation among
patches in local habitats. It is thus the interaction of the trait
(co)-variation and the attributes of the patches in the system
that should most strongly affect the behaviour of the
system. Of course, the distribution of traits among the
species in the regional species pool will be determined by
evolutionary and biogeographic processes, and this would
imply that these larger-scale evolutionary processes would
play an important role in structuring metacommunities.
THE SIGNIFICANCE OF THE METACOMMUNITY
CONCEPT IN ECOLOGY
The metacommunity approach has already provided novel
insights into several well-known aspects of community
ecology. For example, the hypothesis of Ôcommunity-wide
character displacementÕ (CWCD) is that locally coexisting
species should be less similar to each other than those that
would have been expected by random draws from a larger
regional pool. Data consistent with CWCD have been
suggested as evidence for a strong role of interspecific
competition in structuring communities (Diamond 1975).
However, a metacommunity perspective shows that sorting
along gradients in communities might result in just the
reverse pattern, i.e. locally coexisting species should be more
similar than random draws (see Leibold 1998). This
prediction results from the fact that combinations of
species that are more similar in resource use are less
invasible by new species, and these combinations are
therefore more likely to persist in the face of colonization.
The complication is that as coexisting species become more
similar the dynamic stability of the system decreases (see
Abrams 1999 for a detailed contrast between systems with
point equilibria and systems that oscillate in relation to
similarity). Thus the actual outcome of metacommunity
dynamics will depend on how this tension between
invasibility of point equilibria and the dynamic stability of
those equilibria is resolved. If the effect of similarity on
stability is large (perhaps especially if interactions are
nonlinear or if the environment is unstable) then CWCD
is more likely than if the effect of similarity on stability is
small. The metacommunity perspective provides an important modification of the interpretation of CWCD from
purely local theory because it predicts that CWCD should be
associated with non-equilibrium local population dynamics
instead of the more conventional assumption that CWCD
was more likely when local populations were at competitive
equilibria. Patterns consistent with CWCD and patterns
indicating just the opposite have been observed in nature,
even in situations where the patches are relatively homogenous (Gotelli & Graves 1996; Chase & Leibold 2003),
indicating that both ends of the spectrum of results may
exist but studies have not yet focused on metacommunity
interpretations.
A second example is the inference of regional influences
on local communities based on non-asymptotic relationships between local and regional diversity. Classically, the
shape of this relationship has been used to infer whether or
not local communities are ÔsaturatedÕ (i.e. susceptible to
invasions). Recent work using metacommunity theory
(Caswell & Cohen 1993; Loreau 2000; Shurin & Allen
2001; Mouquet & Loreau 2003), however, shows that this
inference is not warranted and that this can depend on
dispersal. The conclusions of these metacommunity models
are supported by direct experimental investigation (Shurin
2000) showing that systems that show non-asymptotic
relations can be strongly saturated (Shurin et al. 2000). One
solution of this apparent paradox is found in a food web
metacommunity assembly model (Shurin & Allen 2001). In
this model predators can prevent some prey species from
coexisting with others via inhibition effects, but they can
also facilitate coexistence among some other prey species.
Ultimately the diversity of the local prey assemblages can
become saturated but the diversity where this occurs is
arbitrary depending on the distribution of prey and predator
traits (see also Grover 1994) and will be greater when the
regional species pool is large, thus facilitating more diverse
local combinations of predators and prey. At the regional
level diverse predators and prey assemblages allow more
heterogeneity in the eventual compositions of local sites,
thus also favouring high regional diversity.
A third case in which a metacommunity perspective can
be useful involves consistent patterns in the distribution of
local vs. regional biodiversity across different gradients. In
relation to productivity gradients, for example, there seems
to be a change in these two types of diversity relations:
diversity of local communities often shows a unimodal
relationship to productivity (e.g. Tilman & Pacala 1993;
Rosenzweig 1995; Leibold 1999) but regional diversity can
simultaneously show a monotonic relationship (e.g. Mittelbach et al. 2001; Chase & Leibold 2002). This can only be
true if turnover among local communities with similar
productivity is much higher at high productivity than at low
productivity. This may occur if high productivity sites tend
to be more heterogeneous among themselves in other
abiotic factors but this is not always obviously so (Chase &
Leibold 2002). However, there are two other possibilities.
One is that alternative stable states are more likely at higher
productivity than at lower productivity and that these
alternative states coexist in a metacommunity (Chase 2003;
Chase & Leibold 2003). A second is that assembly processes
that lead to repeated cyclical changes in composition (rather
Ó2004 Blackwell Publishing Ltd/CNRS
610 M. A. Leibold et al.
than single composition endpoints) are more likely at high
productivity (Steiner & Leibold 2004). Metacommunity
models with varying levels of dispersal also show that
whether there is a unimodal diversity–productivity relationship also depends critically on the assumed form of local
dynamics (Mouquet et al. 2002; Mouquet & Loreau 2003).
One of the more intriguing aspects of current work on
metacommunities is the identification of patterns in
variation of ecosystem attributes over larger spatial scales.
For example, there is evidence that species turnover (or
sorting) is essential in producing the well-documented
scaling relationships in the standing biomass of organisms at
adjacent trophic levels in response to variation in
productivity (Leibold et al. 1997; Chase et al. 2000). Models
that ignore such metacommunity processes indicate that
responses to productivity should be very heterogeneous,
sometimes strongly favouring plants and otherwise strongly
favouring herbivores (e.g. Oksanen et al. 1981; Abrams
1993). Metacommunity structure is important here because
it characterizes the species pool that allows compositional
change to track environmental changes in productivity
(Leibold & Norberg, in press). In the absence of appropriate
Ôplayers in the wingsÕ, changes in productivity strongly
favour either plants or herbivores as predicted by local
models of food webs, but colonization and subsequent
extinctions are what allows food web structure to change in
ways that yield roughly symmetric effects on both plant and
herbivores.
This is a simple example of a broader set of ways in which
metacommunity dynamics might regulate the effects of
biodiversity on ecosystem attributes. Current theoretical and
experimental work is focused on the effects of local diversity
on local ecosystem attributes. However, metacommunity
dynamics can substantially alter our expectations based
solely on a local perspective. For example, in closed local
communities, enhanced diversity is likely to lead to
decreased stability of local communities and, potentially,
of the ecosystems in which they occur (May 1973; Pimm &
Lawton 1978). However, dispersal among different local
communities from a metacommunity with higher regional
biodiversity might stabilize these local dynamics (Mouquet
et al. 2002). An important conclusion is that biodiversity at
larger spatial scales may also be important in regulating the
dynamic behaviour of ecosystems in ways that differ
significantly from currently documented effects of local
diversity.
PROSPECTUS
In this review, we have proposed a definition for metacommunities and we have reviewed four simplistic approaches that have been taken to model them. It is clear from
this review that any synthesis that links these four
Ó2004 Blackwell Publishing Ltd/CNRS
approaches to each other would greatly facilitate empirical
work and would provide a much more realistic framework
for understanding ecology at these larger scales. We have
also tried to show how metacommunity approaches can lead
to substantial changes in the ways we interpret ecological
phenomena, both at the local scale (e.g. the role of source–
sink relations in modifying local diversity) and at the
metacommunity scale (e.g. the role of source–sink relations
in altering regional diversity). More importantly perhaps are
some of the ways that metacommunities show how local
and regional processes interact, such as the relationships
between local saturation of diversity and the correlations
between local and regional diversity. We suspect that
numerous other ecological phenomena will either be
discovered or will be reinterpreted in the context of
metacommunities and view this as an extremely exciting
area for future work. The work is particularly important as
ecologists struggle to find ways to use their usually smallscale studies of ecological processes to make conclusions
about the larger-scale dynamics that are often of greater
environmental concern. For example, Skelly (2002) has
shown that amphibian demography is substantially different
in natural ponds than in studies conducted in closed
mesocosms that are meant to mimic these ponds. While the
causes of these differences are unclear, one possibility is that
dynamical changes in resources, pathogens or parasites
involving metacommunity dynamics operate differently in
the naturally open systems than in the closed mesocosm
analogues.
Clearly the work done on metacommunities to date is still
in its infancy. It is important because it provides a way for
ecologists to seek principles that can explain ecological
patterns at larger scales than in the past. While the work
certainly draws on much ÔclassicÕ work such as island
biogeography and the study of vegetation gradients, novel
insights are coming from two forms of integration. First
there is the inclusion of more realistic community structure
and community ecology into approaches that previously
considered only species diversity, such as much of island
biogeography and explorations of alpha, beta and gamma
diversity. Second and perhaps more important is the novel
integration of community ecology with population dynamic
approaches that have conventionally been limited to the
local scale that is providing new insights.
In this review we have limited our attention of
metacommunity approaches that are not spatially explicit.
In part this is because the literature on spatially explicit
models is becoming much larger than what we could have
reviewed, but in part it is because we are interested in
general approaches that do not strongly depend on spatially
explicit details of systems and of the movements or
organisms. We recognize that spatially explicit models have
an equally important role in extending ecological approaches
The metacommunity concept 611
to larger scales. It is possible that such models could give
better predictions for the behaviour of specific systems than
the generalized metacommunity approach we have reviewed
here. However, even if this is so, it is our contention that
metacommunity models of the type we have described in
this review will be useful in both interpreting these models
and in showing how systems that may have very different
spatial dynamics vary, either by giving convergent results or
by producing different outcomes.
ACKNOWLEDGEMENTS
We thank S. Hall and P. Geddes and two anonymous
referees for comments on earlier drafts of this manuscript.
This work was supported by the National Center for
Ecological Analysis and Synthesis. MH was supported by
NSF DEB-0213026.
REFERENCES
Abrams, P.A. (1993). Effect of increased productivity on the
abundances of trophic levels. Am. Nat., 141, 351–371.
Abrams, P.A. (1999). Is predator-mediated coexistence possible in
unstable systems? Ecology, 80, 608–621.
Abrams, P.A. & Walters, C.J. (1996). Invulnerable prey and the
paradox of enrichment. Ecology, 77, 1125–1133.
Amarasekare, P. (2000). The geometry of coexistence. Biol. J.
Linnean Soc., 71, 1–31.
Amarasekare, P. (2003). Competitive coexistence in spatially
structure environments: a synthesis. Ecol. Lett., 6, 1109–1122.
Amarasekare, P. & Nisbet, R.M. (2001). Spatial heterogeneity,
source–sink dynamics, and the local coexistence of competing
species. Am. Nat., 158, 572–584.
Bell, G. (2000). The distribution of abundance in neutral communities. Am. Nat., 155, 606–617.
Bell, G. (2001). Neutral macroecology. Science (Washington DC), 293,
2413–2418.
Belyea, L.R. & Lancaster, J. (1999). Assembly rules within a contingent ecology. Oikos, 86, 402–416.
Bolker, B., Holyoak, M., Krivan, V., Rowe, L. & Schmitz,
O. (2003). Connecting theoretical and empirical studies of traitmediated interactions. Ecology, 84, 1101–1114.
Boorman, S.A. & Levitt, P.R. (1973). Group selection on the
boundary of a stable population. Theor. Pop. Biol., 4, 85–128.
Brown, J.H. & Kodric-Brown, A. (1977). Turnover rates in insular
biogeography: effect of immigration on extinction. Ecology, 58,
445–449.
Caswell, H. (1976). Community structure – neutral model analysis.
Ecol. Monogr., 46, 327–354.
Caswell, H. (1978). Predator mediated co-existence: a non-equilibrium model. Am. Nat., 112, 127–154.
Caswell, H. & Cohen, J.E. (1993). Local and regional regulation of
species–area relations: a patch-occupancy model. In: Species
Diversity in Ecological Communities (eds Ricklefs, R.E. & Schluter, D.).
Belknap, Cambridge, MA, pp. 99–107.
Chase, J.M. (2003). Community assembly: when does history
matter? Oecologia, 136, 489–495.
Chase, J.M. & Leibold, M.A. (2002). Spatial scale dictates the
productivity–biodiversity relationship. Nature, 416, 427–430.
Chase, J.M. & Leibold, M.A. (2003). Ecological Niches. University of
Chicago Press, Chicago, IL.
Chase, J.M., Leibold, M.A., Downing, A. & Shurin, J.B. (2000).
Effects of productivity, herbivory and plant species turnover in
grassland food webs. Ecology, 81, 2485–2497.
Chesson, P.L. (1985). Coexistence of competitors in spatially and
temporally varying environments – a look at the combined
effects of different sorts of variability. Theor. Popul. Biol., 28,
263–287.
Chesson, P. & Huntly, N. (1997). The roles of harsh and fluctuating conditions in the dynamics of ecological communities. Am.
Nat., 150, 519–553.
Cornell, H.V. & Karlson, R.H. (2000). Coral species richness:
ecological versus biogeographical influences. Coral Reefs, 19,
37–49.
Cottenie, K., Michels, E., Nuytten, N. & De Meester, L. (2003).
Zooplankton metacommunity structure: regional vs. local processes in highly interconnected ponds. Ecology, 84, 991–1000.
Crowley, P.H. (1981). Dispersal and the stability of predator–prey
interactions. Am. Nat., 118, 673–701.
Danielson, B.J. (1991). Communities in a landscape: the influence
of habitat heterogeneity on the interactions between species.
Am. Nat., 138, 1105–1120.
Diamond, J.M. (1975). Assembly of species communities. In:
Ecology and Evolution of Communities (eds Cody, M.L. & Diamond,
J.M.). Belknap, Cambridge, MA, pp. 342–444.
Dobzhansky, T.G. (1951). Genetics and the Origin of Species, 3rd edn.
Columbia University Press, New York.
Drake, J.A. (1991). Community-assembly mechanics and the
structure of an experimental species ensemble. Am. Nat., 137,
1–26.
Forbes, A.E. & Chase, J.N. (2002). The role of habitat connectivity
and landscape geometry in experimental zooplankton metacommunities. Oikos, 96, 433–440.
Gilbert, F., Gonzalez, A. & Evans-Freke, I. (1998). Corridors
maintain species richness in the fragmented landscapes of a
microecosystem. Proc. R. Soc. London Ser. B, 265, 577–582.
Gilpin, M.E. & Hanski, I.A. (1991). Metapopulation Dynamics: Empirical and Theoretical Investigations. Academic Press, London.
Gonzalez, A. & Chaneton, E.J. (2002). Heterotrophic species extinction, abundance and biomass dynamics in an experimentally
fragmented microecosystem. J. Anim. Ecol., 71, 594–602.
Gonzalez, A., Lawton, J.H., Gilbert, F.S., Blackburn, T.M. &
Evans-Freke, I. (1998). Metapopulation dynamics, abundance,
and distribution in a microecosystem. Science, 281, 2045–2047.
Gotelli, N.J. & Graves, G.R. (1996). Null Models in Ecology.
Smithsonian Institution Press, Washington, DC.
Grover, J.P. (1994). Assembly rules for communities of nutrientlimited plants and specialist herbivores. Am. Nat., 143, 258–282.
Hanski, I. (1998). Metapopulation Ecology. Oxford University Press,
Oxford, UK.
Harrison, S. (1997). How natural habitat patchiness affects the
distribution of diversity in Californian serpentine chaparral.
Ecology, 78, 1898.
Harrison, S. & Taylor, A.D. 1997. Empirical evidence for metapopulation dynamics: a critical review. In: Metapopulation
Dynamics: Ecology, Genetics and Evolution (eds Hanski, I. &
Gilpin, A.D.). Academic Press, San Diego, CA, pp. 27–42.
Ó2004 Blackwell Publishing Ltd/CNRS
612 M. A. Leibold et al.
Hassell, M.P., Comins, H.N. & May, R.M. (1994). Species coexistence and self-organizing spatial dynamics. Nature, 370, 290–
292.
Hastings, A. (1980). Disturbance, coexistence, history, and competition for space. Theor. Popul. Biol., 18, 363–373.
Holt, R.D. (1977). Predation, apparent competition, and the
structure of prey communities. Theor. Popul. Biol., 12, 237–266.
Holt, R.D. (1985). Population dynamics in two-patch environments: some anomalous consequences of an optimal habitat
distribution. Theor. Popul. Biol., 28, 181–208.
Holt, R.D. (1993). Ecology at the mesoscale: the influence of
regional processes on local communities. In: Species Diversity in
Ecological Communities (eds Ricklefs, R. & Schluter, D.). University
of Chicago Press, Chicago, IL, pp. 77–88.
Holt, R.D. (1997). From metapopulation dynamics to community
structure: some consequences of spatial heterogeneity.
In: Metapopulation Dynamics: Ecology, Genetics, and Evolution (eds
Hanski, I.P. & Gilpin, M.E.).
Holt, R.D. (2002). Food webs in space: on the interplay of dynamic
instability and spatial processes. Ecol. Res., 17, 261–273.
Holt, R.D. & Polis, G.A. (1997). A theoretical framework for
intraguild predation. Am. Nat., 149, 745–764.
Holt, R.D., Grover, J. & Tilman, D. (1994). Simple rules for
interspecific dominance in systems with exploitative and
apparent competition. Am. Nat., 144, 741–771.
Holt, R.D., Barfield, M. & Gonzalez, A. (2003). Impacts of
environmental variability in open populations and communities:
ÔinflationÕ in sink environments. Theor. Popul. Biol., 64, 315–330.
Holyoak, M. (2000). Habitat subdivision causes changes in food
web structure. Ecol. Lett., 3, 509–515.
Holyoak, M. & Ray, C. (1999). A roadmap for metapopulation
research. Ecol. Lett., 2, 273–275.
Hubbell, S.P. (2001). The Unified Neutral Theory of Biodiversity and
Biogeography. Princeton University Press, Princeton, NJ.
Husband, B.C. & Barrett, S.C.H. (1996). A metapopulation
perspective in plant population biology. J. Ecol., 84, 461–469.
Iwasa, Y. & Roughgarden, J. (1986). Interspecific competition
among metapopulations with space-limited subpopulations.
Theor. Popul. Biol., 30, 194–214.
Kareiva, P. (1990). Population dynamics in spatially complex
environments: theory and data. Philos. Trans. R. Soc. London Ser. B,
330, 175–190.
Kessler, M. (2000). Upslope-directed mass effect in palms along an
Andean elevational gradient: a cause for high diversity at midelevations? Biotropica, 32, 756–759.
Kitching, R.L. (2001). Food webs in phytotelmata: Ôbottom-upÕ and
Ôtop-downÕ explanations for community structure. Ann. Rev.
Entomol., 46, 729–760.
Klausmeier, C.A. (2001). Habitat destruction and extinction in
competitive and mutualistic metacommunities. Ecol. Lett., 4, 57–
63.
Kneitel, J.M. & Chase, J.M. (2004). Trade-offs in community
ecology: linking spatial scales and species coexistence. Ecol. Lett.,
7, 69–80.
Kneitel, J.M. & Miller, T.E. (2002). Resource and top-predator
regulation in the pitcher plant (Sarracenia purpurea) inquiline
community. Ecology, 83, 680–688.
Kneitel, J.M. & Miller, T.E. (2003). Dispersal rates affect species
composition in metacommunities of Sarracenia purpurea
inquilines. Am. Nat., 162, 165–171.
Ó2004 Blackwell Publishing Ltd/CNRS
Kuno, E. (1987). Principles of predator–prey interaction in theoretical, experimental, and natural population systems. Adv. Ecol.
Res., 16, 250–331.
Law, R. & Leibold, M.A. (in press). Assembly dynamics in metacommunities. In: Metacommunity Ecology: Emerging Views of Community Structure and Dynamics Above the Local Scale (eds Holyoak,
M., Leibold, M.A. & Holt, R.D.).
Law, R. & Morton, R.D. (1996). Permanence and the assembly of
ecological communities. Ecology, 74, 1347–1361.
Leibold, M.A. (1996). A graphical model of keystone predators in
food webs: trophic regulation of abundance, incidence and
diversity patterns in communities. Am. Nat., 147, 784–812.
Leibold, M.A. (1998). Similarity and local co-existence of species in
regional biotas. Evol. Ecol., 12, 95–110.
Leibold, M.A. (1999). Biodiversity and nutrient enrichment in pond
plankton communities. Evol. Ecol. Res., 1, 73–95.
Leibold, M.A. & Miller, T.E. (2004). From metapopulations to
metacommunities. In: Ecology, Genetics, and Evolution of Metapopulations (eds Hanski, I. & Gaggiotti, O.E.). Elsevier/Academic
Press, Amsterdam, pp. 133–150.
Leibold, M.A. & Norberg, J. (in press). Plankton metacommunities
as self-organized adaptive systems. Limnol. Oceanogr.
Leibold, M.A., Chase, J.M., Shurin, J.B. & Downing, A.L. (1997).
Species turnover and the regulation of trophic structure. Annu.
Rev. Ecol. Syst., 28, 467–494.
Levin, S.A. (1974). Dispersion and population interactions. Am.
Nat., 108, 207–228.
Levin, S.A. (1992). The problem of pattern and scale in ecology.
Ecology, 73, 1943–1967.
Levins, R. (1969). Some demographic and genetic consequences of
environmental heterogeneity for biological control. Bull. Entomol.
Soc. Am., 15, 237–240.
Levins, R. & Culver, D. (1971). Regional coexistence of species and
competition between rare species. Proc. Natl. Acad. Sci. USA, 68,
1246–1248.
Loreau, M. (2000). Are communities saturated? On the relationship
between alpha, beta and gamma diversity. Ecol. Lett., 3, 73–76.
MacArthur, R.H. (1958). Population ecology of some warblers of
northeastern coniferous forests. Ecology, 39, 599–619.
MacArthur, R.H. & Wilson, E.O. (1967). The Theory of Island Biogeography. Princeton University Press, Princeton, NJ.
Maurer, B.A. (1999). Untangling Ecological Complexity: The Macroscopic
Perspective. University of Chicago Press, Chicago, IL.
May, R.M. (1973). Stability and Complexity in Model Ecosystems.
Princeton University Press, Princeton, NJ.
McCann, K., Hastings, A. & Huxel, G.R. (1998). Weak trophic
interactions and the balance of nature. Nature, 395, 794–798.
McCauley, E., Wilson, W.G. & de Roos, A.M. (1993). Dynamics of
age- and spatially-structured predator–prey interactions: individual-based models and population level formulations. Am.
Nat., 142, 412–442.
McPeek, M.A. & Brown, J.M. (2000). Building a regional species
pool: diversification of the Enallagma damselflies in eastern
North America. Ecology, 81, 904–920.
Mehranvar, L. & Jackson, D.A. (2001). History and taxonomy:
their roles in the core-satellite hypothesis. Oecologia, 127, 131–
142.
Miller, T.E., Kneitel, J.M. & Burns, J.H. (2002). Effect of community structure on invasion success and rate. Ecology (Washington
DC), 83, 898–905.
The metacommunity concept 613
Mittelbach, G.G., Steiner, C.F., Scheiner, S.M., Gross, K.L.,
Reynolds, H.L., Waide, R.B. et al. (2001). What is the observed
relationship between species richness and productivity? Ecology,
82, 2381–2396.
Mouquet, N. & Loreau, M. (2002). Coexistence in metacommunities: the regional similarity hypothesis. Am. Nat., 159, 420–426.
Mouquet, N. & Loreau, M. (2003). Community patterns in source–
sink metacommunities. Am. Nat., 162, 544–557.
Mouquet, N., Moore, J.L. & Loreau, M. (2002). Plant species
richness and community productivity: why the mechanism that
promotes coexistence matters. Ecol. Lett., 5, 56–65.
Mumby, P.J. (1999). Can Caribbean coral populations be modelled
at metapopulation scales? Mar. Ecol. Progr. Ser., 180, 275–288.
Murdoch, W.W. & Oaten, A. (1975). Predation and population
stability. Adv. Ecol. Res., 9, 1–31.
Oksanen, L., Fretwell, S., Arruda, A. & Niemela, P. (1981).
Exploitation ecosystems in gradients of primary productivity.
Am. Nat., 118, 240–261.
Pianka, E.R. (1966). Latitudinal gradients in species diversity: a
review of concepts. Am. Nat., 100, 33–46.
Pimm, S.L. & Lawton, J.H. (1978). On feeding on more than one
trophic level. Nature, 275, 542–544.
Pulliam, H.R. (1988). Sources, sinks, and population regulation.
Am. Nat., 132, 652–661.
Roberts, C.M. (1997). Connectivity and management of Caribbean
coral reefs. Science (Washington DC), 278, 1454–1457.
Rosenzweig, M.L. (1995). Species Diversity in Space and Time. Cambridge University Press, Cambridge, UK.
Schoener, T.W. & Spiller, D.A. (1987). High population persistence
in a system with high turnover. Nature, 330, 474–477.
Schoener, T.W. & Spiller, D.A. (1996). Devastation of prey
diversity by experimentally introduced predators in the field.
Nature, 381, 691–694.
Shmida, A. & Wilson, M.V. (1985). Biological determinants of
species diversity. J. Biogeogr., 12, 1–20.
Shurin, J.B. (2000). Dispersal limitation, invasion resistance, and
the structure of pond zooplankton communities. Ecology, 81,
3074–3086.
Shurin, J.B. (2001). Interactive effects of predation and dispersal on
zooplankton communities. Ecology, 82, 3404–3416.
Shurin, J.B. & Allen, ?? (2001). Effects of competition, predation,
and dispersal on species richness at local and regional scales. Am.
Nat., 158, 624–637.
Shurin, J.B., Havel, J.E., Leibold, M.A. & Pinel-Alloul, B. (2000).
Local and regional zooplankton species richness: a scaleindependent test for saturation. Ecology, 81, 3062–3073.
Shurin, J.B., Amarasekare, P., Chase, J.M., Holt, R.D., Hoopes, M.
& Leibold, M.A. (2003). Alternative stable states and regional
community structure. J. Theor. Biol., 227, 359–368.
Skelly, D.K. (2002). Experimental venue and estimation of interaction strength. Ecology, 83, 2097–2101.
Steiner, C.F. & Leibold, M.A. (2004). Cyclic assembly trajectories
and scale-dependent productivity–diversity relationships. Ecology,
85, 107–113.
Taylor, A.D. (1990). Metapopulations, dispersal, and predator–prey
dynamics: an overview. Ecology, 71, 429–433.
Tilman, D. (1982). Resource Competition and Community Structure.
Princeton University Press, Princeton, NJ.
Tilman, D. (1994). Competition and biodiversity in spatially
structured habitats. Ecology, 75, 2–16.
Tilman, D. & Pacala, S. (1993). The maintenance of species richness in plant communities. In: Species Diversity in Ecological Communities (eds Ricklefs, R.E. & Schluter, D.). University of
Chicago Press, Chicago, IL, pp. 13–25.
Van Nouhuys, S. & Hanski, I. (2002). Multitrophic interactions in
space: metacommunity dynamics in fragmented landscapes. In:
Multitrophic Level Interactions (eds Tscharntke, T. & Hawkins,
B.A.). Cambridge University Press, Cambridge, UK, pp. 124–
147.
Vandermeer, J.H. (1973). On the regional stabilization of locally
unstable predator–prey relationships. J. Theor. Biol., 41, 161–170.
Weiher, E. & Keddy, P. (eds.) (1999). Ecological Assembly Rules,
Advances, Retreats: Perspectives. Cambridge University Press,
Cambridge.
Whittaker, R.H. (1962). Classification of natural communities. Bot.
Rev., 28, 1–239.
Wiens, J.A. (1989). Spatial scaling in ecology. Funct. Ecol., 3, 385–
397.
Wilson, D.S. (1992). Complex interactions in metacommunities,
with implications for biodiversity and higher levels of selection.
Ecology, 73, 1984–2000.
Worthen, W.B., Carswell, M.L. & Kelly, K.A. (1996). Nested subset
structure of larval mycophagous fly assemblages: nestedness in a
non-island system. Oecologia, 107, 257–264.
Yu, D.W. & Wilson, H.B. (2001). The competition-colonization
trade-off is dead; long live the competition-colonization tradeoff. Am. Nat., 158, 49–63.
Yu, D.W., Wilson, H.B. & Pierce, N.E. (2001). An empirical model
of species coexistence in a spatially structured environment.
Ecology (Washington DC), 82, 1761–1771.
Editor, Howard Cornell
Manuscript received 13 February 2004
First decision made 14 March 2004
Manuscript accepted 7 April 2004
Ó2004 Blackwell Publishing Ltd/CNRS